OpenNMT, the Neural Translation System, developed by SYSTRAN and Harvard, distinguished by ACL 2017, The World Conference of Experts in Computer Linguistics

2017-08-10 09:00

SEOUL, South Korea, Aug. 10, 2017 /PRNewswire/ -- SYSTRAN, a software publisher specialized in machine translation and natural language processing, announces that the joint research and development between SYSTRAN and Harvard NLP on neural translation has been distinguished by the ACL, the 55th World Conference of Experts in Computer Linguistics. The article summarizing this research was awarded "Best Demonstration Runner-up" (finalist in the category of operational systems). This rewards a commitment of more than six months by the SYSTRAN R&D teams and recognizes the excellence of their research.

The ACL is the world's leading meeting on research on automatic language processing. This year, the ACL was held in Vancouver from July 30 to August 4, 2017 and highlights the latest advances in artificial intelligence applied to language processing: neural translation, semantic analysis, automatic content generation. This year, ACL has decided to reward, among others, research projects that are distinguished by their excellence and their innovative character.

Open Neural Machine Translation, developed by SYSTRAN and Harvard, distinguished by ACL

In the "Operational Systems" category, the OpenNMT system developed by SYSTRAN and Harvard is one of the two finalist projects, ahead of dozens of other innovative projects representing the elite of international research. OpenNMT is an open source neural translation system, launched in December 2016, with several hundred users and contributors from the academic and industrial world. About twenty researchers, linguists and engineers from SYSTRAN's R&D, are working on the development of this platform and enlivening the user community.

An important step for SYSTRAN

The mastery of neuronal technology by SYSTRAN and the positive reception by the market augurs very important development prospects. With GAFAM, embarking on the development of similar solutions, SYSTRAN, always a forerunner, has already obtained the recognition of the scientific community and is moving on to the next stage. The company now wants to capitalize on these developments to open up new possibilities, beyond automatic translation, in other areas such as semantic analysis, multimedia document processing, or language learning. To feed these ambitious projects, SYSTRAN is currently recruiting experts to expand its R & D department, particularly in the field of Artificial Intelligence.

Jean Senellart, Global CTO (Technical Director & Global Innovation) of the SYSTRAN Group comments on this distinction: "OpenNMT is at the crossroads of academic research and industrial requirements in an Open source context. This recognition enhances the work done by researchers, engineers and all of the user-contributors federated through this project. In an Open source project, a constant and long-term commitment is essential to gain the support of the community. It is this day-to-day commitment by the SYSTRAN R&D teams that is now rewarded. Nevertheless, the best is still ahead of us: in the months and years to come, our customers will be

able to benefit from the incredible potential offered by these latest innovations. "

About SYSTRAN

SYSTRAN machine translation solutions enable companies to improve their multilingual communication and productivity in many areas such as in-house collaboration, Big Data management, monitoring, e-discovery, content management, customer support, E-commerce and localization projects. With more than 140 language pairs available, SYSTRAN solutions, which are secure and customized in every customer context, are used daily by many global companies, organizations in the defense and security sector, and translation agencies.

Since its creation SYSTRAN has always been a pioneer in automatic language processing and today offers the market a new generation of engines by exploiting the latest advances offered by artificial neural networks and Deep Learning.